An empirical study on the preference and satisfaction for the pre-paid and post-paid cellular subscribers.

Misra, Richa

Introduction

As markets become saturated and competition intensifies, customers have more choices and are eager to flex their purchasing power. Churn rates have escalated with increased competition and regulation. Churn is the greatest problem telecoms are facing in this competitive environment. Operators/ that choose not to take a proactive approach to minimizing churn will never achieve a stable customer base and will not be able to attain their revenue potential and lag behind in competition.

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With ten players already present (including the old and new venture) in Delhi-NCR Airtel, Vodafone, Dolphin-Garuda, Idea, Reliance, TataDocomo, Aircel, Uninor, MTS, Etisalat the telecommunication market has become more competitive than ever.

For service providers increased customer churn has resulted in rising customer acquisition cost and lower average monthly billing. In this scenario the service provider has to play an ongoing role in keeping customer happy and they proactively need to identify high value customer who are thinking of switching and develop ways to retain them. To meet these challenges service providers are employing CRM and data mining technique. The telecom industry has used CRM packages to gather the data at various touch points of customer interaction however often the data have not been effectively utilized for effective customer relationship and business growth.

The study aims to provide a comprehensive assessment of the satisfaction of subscribers with the services received from their current service provider and explores the difference in perception between subscribers using prepaid and postpaid contracts on the basis of various business and technical dimensions. According to Research Firm Gartner, India's Churn rate is 4.5 to 8.0 percent per month, which is one of the highest in Asia Pacific Region. Gartner Group shows that it costs 5-6 times more to recruit a new customer than to retain an existing one, customer retention has now become even more important than customer acquisition. For many incumbent operators, retaining high profitable customers is the number one business plan.

In order to support telecom companies manage churn reduction, not only do we need to predict which customers are at high risk of churn, but also we need to know how soon these high-risk customers will churn. Therefore the telecom companies can optimize their marketing involvement resources to prevent as many customers as possible from churning. In other words, if the telecom companies know which customers are at high risk of churn and when they will churn, they are able to design customized customer communication and treatment programs in a timely efficient manner.

The Role of Prepaid Cellular Subscribers

The objective of prepaid contract by cellular service provider was to serve the need of credit challenged subscribers. Prepaid contract was like a win-win offering for the service providers as there was no credit risk as no such facility was offered to these customers. The principal benefit for choosing a pre-paid connection for the subscriber is that there is no contract a subscriber can cancel the contract anytime without paying any penalty. For a prepaid subscriber connecting to a cellular service provider is as simple as buying a SIM card from a local vendor or a grocery shop. Prepaid Service contract was also friendly for the subscribers as they get a mobile connection with least documentation. According to TRAI prepaid services are 20 percent cheaper than postpaid services. Prepaid Cellular Subscribers have the flexibility to top up their credit at their time of convenience and a variety of payment mechanisms are also available. Subscriber's has more control over their billing as balance can be queried at any time.

The Indian telecom market has more than 91 percent prepaid subscribers and they change networks at an astounding 50 to 70 percent. The postpaid market for mobile operators in India is just 9 percent of total subscriber base but contributes 20 percent to the total subscriber revenue. (Gartner Report 2010)

Now the prepaid segment is the dominant and fastest growing segment in India especially in the rural market. Churn in the prepaid segment is much higher than churn in the postpaid segment - sometimes around 3 times the churn in the postpaid segment. A very promising loyalty strategy that has emerged in India is the lifetime incoming guarantee for prepaid subscribers.

Review of Literature

Churn

Churn the movement of customers from provider to provider in search of better and cheaper products and services. The term is used widely but is adopted conceptually in the Cellular Subscription Market. The churn rate is one of the most critical subject for this industry. This is due to the fact that cellular service providers don't differentiate from each other. They all deliver more or less the same service and competition is heavy.

All service providers are looking for loyal and satisfied customers. As markets become saturated and competition intensifies, customers have more choices and are eager to flex their purchasing power. In the telecom industry, the broad definition of churn is the action that a customer's telecom service is canceled or hung. This includes both service-provider initiated churn and customer initiated churn. An example of service-provider initiated churn is a customer's account being closed because of payment default. Customer initiated churn is more complicated and the reasons behind vary. Examples of reasons are: unacceptable call quality, more favorable competitor's pricing plan, misinformation given by sales, customer expectation not met, billing problem, moving, and change in business, and so on.

Specifically, churn is the gross rate of customer loss during a given period. Churn can be shown as follows:

Monthly Churn = (C0 + A1 - C1) / C0 Where:

C0 = Number of customers at the start of the month

C1 = Number of customers at the end of the month

A1 = Gross new customers during the month

A high churn rate also puts pressure on companies to win new customers. To illustrate how the cost of churn affects an individual wireless carrier, suppose the carrier has three million subscribers at the start of a year and an annual churn rate of 27 percent, amounting to a loss of about 810,000 subscribers in that year. The main problem with customer initiated churn is that customers don't announce their intentions in advance. It's up to the carrier (Mobile Network Operator) to uncover evidence of potential churn, ideally even before the customer solidifies feelings or intentions.

Customer Satisfaction

Customer satisfaction is a well known and established concept in several areas, such as marketing, consumer research, economic psychology, welfare-economics, and economics. The present study also measures customer satisfaction of the cellular service subscribers on the basis of various service quality criterions.

There have been many studies on customer satisfaction over the years. Cardozo (1965) was the first to research this concept and to introduce it into the marketing field. Since then the definition changed over time but it was always clear that satisfaction and quality are interchangeable. Parasuman, Zeithaml and Berry (1994) have provided the clearest definition for satisfaction. They suggest that satisfaction is influenced by service quality, product quality and price. They have researched satisfaction on a transactional level, which implies that the overall satisfaction is a function of transactions.

Satisfaction is a consumer response that is both affective and cognitive. The response has a particular focus and occurs at particular time (Giese and Cote, 2000).

The focus of consumer satisfaction is to compare performance to a standard. The focus can be on different objects like the salesperson, the product or service (or both) and consumption. The focus depends on the context of satisfaction judgment. Satisfaction is known to be a post-purchase phenomenon.

According to Dick and Basu (1994), loyal customers are less likely to search for alternatives and more often engage themselves in word-of-mouth communications with other people. A lot of studies have been conducted on customer loyalty and customer retention and switching behaviour. In fact; switching, loyalty and retention are all constructs in the same area. Where loyalty is positive behaviour, switching can be characterised as negative behaviour. Satisfaction has proven to be strongly related to loyalty (Hallowel, 1996). A study by (Lim, Widdows, Park; 2006) showed that especially in the cellular service market, satisfaction leads to loyalty.

The study about customer loyalty, conducted in Turkey (Aydin and Ozer, 2005) shows that switching costs and service quality are the most important factors for determining customer loyalty.

Customer Knowledge and Retention

The customer knowledge can be used to actively monitor usage patterns to highlight those customers most likely to migrate to another Mobile Network Operator. Analytical customer management strategies are ideal for mobile network operators because they have unusually rich customer transactional data, which allows I very specific patterns and results to be identified.

The tools for performing such analysis of customers include data warehousing, data mining, and data visualization.

Data mining refers to using automatic or semiautomatic methods to extract latent, unknown, meaningful, and useful information or models from large datasets (Berry et al., 2004; Dunham, 2003; Fayyad et al., 1996; Han et al., 2001; Kantardzic, 2003; Tan et al., 2006). Data mining tools identify pattern in data and deliver valuable new information that can increase a company understanding of itself and its customers. Data mining is commonly used to help analysts search for information they don't yet know to look for, often involving no hypothesis. It has helped companies uncover a diverse set of new knowledge. Data mining is the method of penetrating through enormous amount of customer data to discover patterns, associations, and tendency in customer usage. Data mining can assist the service provider to build up customer outline and identify historical relationship between certain outlines and the susceptibility to churn or move to another service provider. Data mining methods are used to investigate many outline-related variables, counting those linked to demographics, service contract, offers and promotion, and usage patterns including feature usage.(Carl Geppert 2002).

It is crucial in such a low margin and tough competition that data mining results extend beyond obvious information. Off-the-shelf data mining solutions may provide minute "new" information and thus supply simply to predict the obvious (e.g., predicting propensity to churn for a subscriber who hasn't paid his or her bills in last three months).

Tailored data mining software's may give much more valuable information to the service provider.

Data visualization software facilitate service provider to view graphically the association between churn and customer outline or outline-related variables. By facilitating human perception to identify relationships that are complex to find out mathematically, visualization present a cognitive accompaniment to statistical methods. In addition to presenting the information Data visualization is a competent mode to study graphically the strength of the associations identified by data mining. Leading indicators of churn potential include late payments, numerous customer service calls, numerous tariff option available to customers and declining use of services. (Wei and Chiu 2002)

There are principally three types of data mining technique particularly to CRM:

Predictive Analysis

In this technique the organization uses historical data to determine future behaviors. Predictive modeling generates output that populates a "model" or structure to represent the results. For instance, a predictive model can indicate the next offer a consumer is most likely to respond, based on historical behavior by the consumer and other consumers who have also responded to the similar offers. It is primarily used to determine future results.

A decision tree is a mining technique based on predictive modeling and as the name suggests, it can be viewed as a tree. Particularly each branch of the tree is the classification question and the leaves of the tree are considered as subsets of the dataset along with their classification. For example in our case we need to segregate the subscriber who are likely to churn a decision tree might be prepared like that in Figure 1.

Neural Networks

Two of the most used data mining algorithms in business are either decision trees or neural networks. Neural networks have both limitation as well as benefits like user friendly and ease of deployment, but they do also have some significant advantages. The most important benefit is their extremely precise predictive models that can be functional across a huge number of significantly distinct issues.

To be more particular with the term "neural network" the term" artificial neural network" is used. True neural networks are natural systems (brains) that discover patterns, can make possible predictions and have the ability to learn. The artificial ones are human created computer programs that design and implement complex pattern discovery and machine learning algorithms on a system to construct predictive models derived from huge historical databases. The genesis of Artificial neural network started off with the hypothesis that systems could be made to "think" if Artificial intelligence found methods to imitate the organization and operation of the human brain on the computer. Henceforth neural networks grew out of the area of Artificial Intelligence instead from the area of statistics.

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Sequential Analysis

This technique records combination of activities that occurs in a particular order. The organization uses sequential analysis to find out whether the consumer is following a particular order. For example a cellular service provider can understand more about a subscriber for the reasons of the slowdown in the usage of cellular services.

Association Analysis

In this algorithm the statistician identifies group of similar activities or items. This technique is frequently used in market basket analysis to help marketer understand the products being purchased together.

While all Cellular Service Provider have proprietary customer information databases, the warehousing and mining of the data can either be performed in-house with the requisite technology platform or outsourced to a telecomfocused CRM adviser. In fact, an advance in CRM technology gives the service provider a choice among a wide range of software packages and customized solutions. In any case, ongoing analysis of real-time data enable a Cellular Service Provider to arbitrate with a range of customer retention options.

Data Mining Solutions Used by Cellular Service Provide

The churn management issue is more intensive in the prepaid cellular contracts, which now a days covers for the immense amount of Indian cellular users. The prepaid customer is more price-sensitive than the post-paid one. With one of the lowest rental world wide, customers with low usage prefer prepaid cards. Also, students and those who like to experiment with different networks prefer the prepaid offering.

According to Express Computer (22 September, 2003) the major cellular service providers have I put into practice SAS's churn management system to decrease churn and maintain profitable subscribers.

SAS data mining and churn management solution provides complete end-to-end customer maintenance solution, which ropes the entire procedure of managing churn-starting from collecting the user's/subscriber's 'data and warehousing the subscribers data in predictive churn model to create reports and suggesting quantified results to cellular service providers to retain their valuable subscribers.

The data mining s/w allow a cellular service provider to get an extensive understanding and knowledge of the variables that impact subscriber's churn. The software allow the telecom operators to study and know which subscriber is prone to switch and the possible reasons behind it, this knowledge enables the cellular service provider to take effective step before the subscriber decides to leave.

The strategy to predict the switching behavior of the subscriber is based on scoring technique. The score is measured on a scale of 0 to 1. If a subscriber scores 0.53 it infers there's a 53 percent propensity of his/her churning or leaving the current service provider. The lesser the score on data mining solution, the more satisfied is the subscriber. After the scores are calculate, it is comparatively likely to find out the subscribers who are more prone to switch.

The churning management solution based on data mining technique enables the cellular operator with a sliced and diced view of the subscribers base, and henceforth it gives power to service provider it to differentiate individual subscriber as per their requirements. The subscriber attributes that are normally accounted in a churn investigation are subscriber demographic information, their payment contract, customer service data, billing and usage data. Out of these the most critical variables that are used historically are the amount of time a subscriber spends on air, the number of voice calls he makes, VAS usage and the bill generated from that subscriber.

The score generated by the solution that provides critical information becomes immensely important for the service provider and henceforth gives them a window to make proactive decisions and subscriber dissatisfaction that are hindrance in service quality and thereby responsible for churn. The sliced and diced data also provides the service provider other benefits and contributes to increase the average revenue per user by providing crossselling and up-selling opportunities, which can further increase the profitability of the service provider. (Atul Jhamb,2003). BHARTI AIRTEL has developed such a fine-grained segmentation approach by applying data mining and predictive analytic techniques to its customer and usage data. This segmentation drives the whole customer lifecycle, from acquisition to retention and development. With customers from urban professionals to rural villagers whose phone is their only technology, segmentation is a pre-requisite for effective targeting. BHARTI AIRTEL customers have access to something called My Airtel, My Offer. Driven by sophisticated predictive analytics and Bharti Airtel's precise segmentation of its customer base, My Airtel, My Offer predicts the best possible plan for each customer. These personalized plan suggestions are presented consistently across Bharti's 20,000 call center representatives, its million plus retail partners and direct to consumers through interactive voice response and SMS systems among others. (James Taylor 2010)

Research Questions

Are there significant underlying differences between prepaid and postpaid cellular subscribers which may lead to churning behavior and price tolerance?

Objectives of the study

The objectives of this study are:

* To identify possible differences in perception of the prepaid and postpaid cellular subscribers for the fundamental attributes of selecting a service provider, Cellular usage and Service quality.

* To identify the usage of data services provided by the service providers.

Research Methodology

Although the number of mobile users is proliferating, there is little empirical evidence to help marketers fully understand what constitutes consumer satisfaction, factors for churning, customer retention and loyalty from a Mobile Network Operator perspective.

The principal sources of data for this exploratory research were based on the review of literature and an experience survey also known as key informant technique to tap the knowledge of those familiar with the subject matter in the chosen set of organizations.

Sample Design

The target population for this study was defined as individuals using an active mobile service in NCR region at the time the survey was conducted. To establish the sample frame, a list of users was obtained from education (students, teaching and administrative Staff), government and corporate institutions and home users of the four major regions: Noida, Delhi, Ghaziabad and Faridabad. It was clearly communicated to the respondents that their opinions should reflect their personal/official usage of the Mobile phone and other related services. Convenience sampling was used as this research sought to generalize the results obtained as much as possible. A total of 500 respondents from the four regions mentioned above.

Service providers have introduced a plethora of value-added services to increase customer 'stickiness'. The common services offered by almost all operators include SMS, group messaging, voice mail, caller line identification, entertainment services and even multimedia messaging. Other than this, different service providers have introduced unique services for certain segments of customers, depending on their usage patterns.

Finding and Interpretation

With the growing acceptance and usage of services other than voice will be the additional revenue generator for the service provider. While the user at large are still comfortable with the basic value added services like SMS (Short Message Service), Picture Messaging (Multimedia Message Service) and Roaming (cellular services in a foreign network) but with the growing importance of social media in organization and in person the advance value application is growing and will further accelerate in near future.

Results and Interpretation

The result in the Table shows that there is a significant difference in the usage of Value Added Service as indicated by Independent sample t-test at 99 percent level of significance.

The rating for the post paid subscribers is higher (Mean=4.61, S.D=2.21) than those for pre-paid (Mean=4.10, S.D=1.78).There is more usage of Value Added Services in the Post Paid group as compared to prepaid group. The reason may be more disposable income in hand as well as more corporate connection in the post paid group subsequently the users need to be connected with the organization there by increased usage of VAS like roaming, official mails.

Regarding the second indicator i.e. Actual Experience, the result shows there is no significant difference found between two groups in the AEXP (Actual Experience Indicator) as indicated by Independent sample t-test. However the mean value indicates Prepaid group is slightly more satisfied (Mean=27.23, S.D=4.33) than the post paid group (Mean=26.52, S.D=4.64) the reason may be no billing complaint in prepaid there by clarity in billing and less complaints as well as prepaid subscribers are receiving the same quality of services in comparatively lesser tariff.

The result of the third Indicator i.e., Mobile Usage shows there is no significant difference found between two groups (Pre-paid and Post-paid) however the mean value indicates in prepaid group (Mean = 10.93, S.D= 4.46) there is slightly more usage of services in terms of SMS than Postpaid (Mean = 10.44, S.D= 4.23) the reason may be more number of students belongs to prepaid group where there is more tendency of making text messages.

The cost indicator result shows there is no significant difference found in this group thereby behavior of both prepaid and postpaid group is similar. However the mean value shows prepaid customers (Mean=8.91, S.D= 1.39) are slightly more satisfied in the cost (indicator) than the postpaid customers (Mean=8.81, S.D= 1.54) the reason may be prepaid customers are no credit customers thereby less billing complaints. Prepaid services may achieve greater control over their expenditure by only making calls they have previously paid there by managing the risk of unpredictable phone bills.

As far as the fundamental attributes of selecting a service provider is considered, the result shows that there is a significant difference found in the pre-purchasing quality indicator in the behavior of two groups prepaid and postpaid. Prepaid subscribers have more pre-purchasing expectation from their service providers as compared to Post-paid subscribers. The reason may be in this segment there are more price sensitive youth market who are relatively more conscious about Cost (Tariff) and VAS.

Conclusion

The telecommunication services have made a rapid stride both in quality and quantity. However the users at large are found dissatisfied with the quality of service made available to them. The process of technological sophistication has gained the momentum but the users are yet to get the quality service.

The study reveals that prepaid customers are significantly more cost conscious as compared to the post paid customers and they have shown significantly more chances of switching if the service provider is increasing the price or the competitor is lowering the price. For Prepaid Customers being on the same network as friends or family is significantly more important. Prepaid customers are significantly more satisfied with quality/price factor; they are also significantly more satisfied with Value Added Services. Prepaid product was like a win-win offering to the service provider as they were not required to take any credit risk, as no credit facility was offered. Mobile service providers have traditionally focused more of the churn management and retention effort on post paid segment and therefore the service providers should design proactive retention program and should make effective use of business intelligence and data mining technologies to stop churning in this segment especially of the profitable customers.

Lowered call tariff and the quality of services including network coverage, line and sound quality was the major industry growth driver. Wireless Subscriber growth will continue as there is still a lot of scope in the Indian rural market. Churn Management in the Prepaid and the Post paid segment need to be proactive rather than reactive because prepaid subscribers are difficult to reach once they leave their service provider. Operators are experiencing low Average revenue per user because of lowered call tariff thus they are focusing upon content aspect. Games and content should be developed keeping local taste in mind.

SMS based application and services are successful. (Reality Shows)

It is imperative to bring value and satisfaction to the subscriber and introduce services and offers that hook the subscriber to their service provider. New technology, continuous improvement in service and development is fundamental to increase loyalty and reduce churn. A churn management solution would definitely provide insights to the service providers and help create more striking incentives, attractive tariff bundles, loyalty schemes and proactive approach customer service in addition to acquisition strategies to attract and retain the right type of subscriber, thus minimizing fraud and bad debt.

Limitation and Scope for Future Research

With respect to future research initiatives, several avenues can be explored. First, a large-scale study utilizing a large data sample is required to further confirm the viability and applicability of the solution.

As per the future research initiative, other opportunities can be explored like a large scale survey of several thousand subscribers on the questions related to Customer satisfaction indicators within a short period of time as the subscriber perception changes due to the effect of external variables. Longitudinal study will be critical to understand the evolution of the behavior of the subscriber over a period of time.

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Richa Misra Assistant Professor, Jaipuria Institute of Management, Noida.

Table I

Usage of Value Added Services Provided
by the Service Providers

Value Added Service              Frequency   Percentage

Download Games                   112         22.4
Text messaging (SMS)             457         91.4
Picture Messaging (MMS)          187         37.4
Voice Mail                       89          17.8
Download ring tones and icons    121         24.2
Wireless internet access         156         31.2
Roaming                          304         60.8
Information services             102         20.4

Table II

Difference in Perception Between Two Groups (Pre-Paid and Post Paid
Group) with Respect to the Customer Satisfaction Indicators

                                      Pre paid         Post paid
Indicators                            (N = 318)        (N = 182)

                                     Mean     SD      Mean     SD

1-Value Added Services              4.10     1.78    4.61     2.21

2-Actual Experience                 27.23    4.33    26.52    4.64

3-Usage of the mobile phone         10.93    4.46    10.44    4.23

4-COST (Cost incurred on the        8.91     1.39    8.81     1.54
services)

5-QUALITY (Fundamental attributes   21.15    4.10    1.78     2.98
of selecting a service provider)

                                      t-value
Indicators                          Significance

1-Value Added Services              2.86    S **

2-Actual Experience                 1.73    NS

3-Usage of the mobile phone         1.19    NS

4-COST (Cost incurred on the        .78     NS
services)

5-QUALITY (Fundamental attributes   2.13    S **
of selecting a service provider)

Note: ** -significant at .001, * -significant at.005,
NS-Not Significant